Remote ML Intern: Ship State-of-the-Art Models

Avenue.io Inc.; Toronto, Montreal; Hybride; CAD 34 000 - 55 000; Plein temps

Avantages offerts par ce poste

Lunch stipend

Health and dental benefits

RRSP matching / pension plan

Parental leave top-up

Enrichment benefits (conferences, etc)

6 weeks of paid vacation

Travel budget for offices + annual off

$500 home office stipend

Résumé du poste

Cohere is seeking a Machine Learning Intern in Canada (Alberta region) for a 3–6 month full-time internship. You will design, train and improve state-of-the-art models, explore new training techniques, and work with product teams to deliver practical NLP solutions.

This is a remote-friendly opportunity with a strong emphasis on learning from experienced staff. Eligible candidates are enrolled post-secondary students, with proficiency in Python and ML frameworks, and experience with large-scale

Qualifications

• Currently pursuing a post-secondary program as a student.
• Internship is full-time for 3–6 months.
• Proficiency in Python and ML frameworks such as TensorFlow, TF-Serving, JAX, XLA/MLIR.
• Experience with large-scale distributed training.
• Familiarity with autoregressive sequence models (Transformers).
• Strong communication and problem-solving skills.
• Bonus: CUDA kernels, TPUs, and published papers at top venues.

Responsabilités

• Design, train and improve cutting-edge models.
• Develop techniques to train and deploy models safely and efficiently.
• Train very large models on massive datasets.
• Explore continual and active learning for streaming data.
• Learn from senior ML staff and collaborate with product teams.

Connaissances

Python

TensorFlow

JAX

XLA/MLIR

Formation

Post-secondary student (enrolled)

Outils

CUDA

TPU

Description du poste

Cohere is seeking a Machine Learning Intern in Canada (Alberta region) for a 3–6 month full-time internship. You will design, train and improve state-of-the-art models, explore new training techniques, and work with product teams to deliver practical NLP solutions.

This is a remote-friendly opportunity with a strong emphasis on learning from experienced staff. Eligible candidates are enrolled post-secondary students, with proficiency in Python and ML frameworks, and experience with large-scale